• Journal of Korea Water Resources Association
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• v.44 no.10
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• pp.843-851
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• 2011

In hydrology, it is appropriate to use probabilistic method for forecasting mid/long term streamflow due to the uncertainty of input data. Through this study, it is expanded mid/long term forecasting system more effectively adding priory process function based on PDF-ratio method to the RRFS-ESP system for Guem River Basin. For implementing this purpose, weight is estimated using probabilistic weather forecasting information from KMA. Based on these results, ESP probability is updated per scenario. Through the estimated result per method, the average forecast score using ESP method is higher than that of naive forecasting and it confirmed that ESP method results in appropriate score for RRFS-ESP system. It is also shown that the score of ESP method applying revised inflow scenario using probabilistic weather forecasting is higher than that of ESP method. As a results, it will be improved the accuracy of forecasting using probabilistic weather forecasting.

• Journal of the Korean Data and Information Science Society
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• v.23 no.5
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• pp.905-912
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• 2012

We are dealing with the Bayes' rule education tool with Excel Macro and its usage example. When an event occurs, we are interested in whether it does under certain conditions or not. In this case, we use the Bayes' rule to calculate the probability. Bayes' rule is very useful in making decision based on newly obtained statistical information. We introduce an efficient self-teaching educational tool developed to help the learners understand the Bayes' rule through intermediate steps and descriptions. The concept and examples of intermediate steps such as conditional probability, multiplication rule, law of total probability, prior probability and posterior probability could be acquired through step-by-step learning. All the processes leading to result are given with diagrams and detailed descriptions. By just clicking the execution button, users could get the results in one screen.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.5
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• pp.412-417
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• 2013

Analytical modeling of photovoltaic power systems has been receiving significant attentions in recent years in that it is easy to apply for prediction of its dynamics and fault detection and diagnosis in advanced engineering technologies. This paper presents a novel probabilistic modeling approach for such power systems with a big data sequence. Firstly, we express input/output function of photovoltaic power systems in which solar irradiation and ambient temperature are regarded as input variable and electric power is output variable respectively. Based on this functional relationship, conditional probability for these three random variables(such as irradiation, temperature, and electric power) is mathematically defined and its estimation is accomplished from ratio of numbers of all sample data to numbers of cases related to two input variables, which is efficient in particular for a big data sequence of photovoltaic powers systems. Lastly, we predict the output values from a probabilistic model of photovoltaic power systems by using the expectation theory. Two case studies are carried out for testing reliability of the proposed modeling methodology in this paper.

• Journal of the Korean Data and Information Science Society
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• v.22 no.4
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• pp.651-660
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• 2011

This study aims at improving teaching and learning abilities on the courses of probability/statistics in the fields of the S/W and H/W. In order to do this, this paper firstly conducts a survey which measures the perception of the surveyees' necessity of the related courses, and includes the contents that the related courses should cover. Secondly, this paper analyzes the educational effect on the achievement by studying Pattern Recognition, a major course of S/W and H/W, with combining probability/statistics or data analysis. Lastly, this paper suggests the promising pedagogical method for educating probability/statistics by using a survey and the case studies. In this way, this paper shows the necessity of probability/statistics for acquiring a new technology and the flexible approach of various subjects.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.37 no.5
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• pp.29-44
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• 2000

Adaptation of operator probabilities is one of the most important and promising issues in evolutionary computation areas. This is because the setting of appropriate probabilities is not only very tedious and difficult but very important to the performance improvement of genetic algorithms. Many researchers have introduced their algorithms for setting or adapting operator probabilities. Experimental results in most previous works, however, have not been satisfiable. Moreover, Tuson have insisted that “the adaptation is not necessarily a good thing” in his papers［$^1$$^2$］. In this paper, we propose a self-tuning scheme for adapting operator probabilities in genetic algorithms. Our scheme was extensively tested on four function optimization problems and one combinational problem； and compared to simple genetic algorithms with constant probabilities and adaptive genetic algorithm proposed by Srinivas et al［$^3$］. Experimental results showed that our scheme was superior to the others. Our scheme compared with previous works has three advantages： less computational efforts, co-evolution without additional operations for evolution of probabilities, and no need of additional parameters.

• The Korean Journal of Financial Management
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• v.8 no.2
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• pp.165-208
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• 1991

This paper develops an intertemporal general equilibrium model of asset pricing with taxes under the noisy and the incomplete information structure and examines theoretically the stochastic behavior of general equilibrium asset prices in a one-good, production, and exchange economy in continuous time markets. The important features of the model are its integration of real and financial markets and the analysis of the effects of differential tax rates between ordinary income and capital gains. The model developed here can provide answers to a wide variety of questions about stochastic structure of asset prices and the effect of tax on them.

• The Korean Journal of Applied Statistics
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• v.29 no.2
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• pp.321-330
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• 2016

Run expectancy (RE) is the mean number of runs scored from a specific base runner/outs situation of an inning to the end of the inning. Win expectancy (WE) is the probability that a particular team will win the game at a specific game state such as half-inning, score difference, outs, and/or runners on base. In this paper, we derive RE and WE for the Korea Baseball Organization (KBO) League based on six-year data from 2007 to 2012 using a Markov chain model.

• Journal of Korea Water Resources Association
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• v.50 no.8
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• pp.563-577
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• 2017

As the uncertainty of precipitation increases due to climate change, seasonal forecasting and the use of weather forecasts become essential for efficient water resources management. In this study, the categorical probabilistic long-term forecasts implemented by KMA (Korea Meteorological Administration) since June 2014 was evaluated using assessment indicators of Hit Rate, Reliability Diagram, and Relative Operating Curve (ROC) and a technique for obtaining quantitative precipitation estimates based on probabilistic forecasts was proposed. The probabilistic long-term forecasts showed its maximum predictability of 48% and the quantified precipitation estimates were closely matched with actual observations; maximum correlation coefficient (R) in predictability evaluation for 100% accurate and actual weather forecasts were 0.98 and 0.71, respectively. A precipitation quantification approach utilizing probabilistic forecasts proposed in this study is expected to enable water management considering the uncertainty of precipitation. This method is also expected to be a useful tool for supporting decision-making in the long-term planning for water resources management and reservoir operations.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.432-432
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• 2017

국내에서 설계홍수량 산정시, 실무 적용성이 높은 설계강우-유출 모형을 채택하고 유출모형으로는 단위도 방법을 적용하여 설계홍수량을 산정한다. 설계홍수량을 산정함에 있어 설계강우-유출관계 모형을 적용하기 위한 필수요소로 확률강우량 산정이 선행되어야 한다. 확률강우량은 유역면적이 25.9 m를 초과할 경우 면적평균확률강우량을 사용하여야하나 지점평균확률강우량을 주로 사용하고 있다. 이는 해당 유역 강우의 공간적 분포를 고려하고 있지 않기 때문에 각 강우관측소에서 관측되는 지점 강우자료를 면적평균확률강우량으로 산정하는데 매번 복잡한 자료처리과정을 거쳐야 하는데 있다. 따라서 비교적 산정이 간편한 지점평균확률강우량을 사용하여 면적평균확률강우량으로 손쉽게 전환할 수 있는 각 유역별 ARF(Areal Reduction Factor) 의 필요성이 대두된다.(이등, 정등 2002) 본 연구에서는 일반적으로 유역의 강우 빈도해석시 이용되는 면적고정형 방법을 사용하여 표본면적에 대하여, 설계홍수량 산정요령(국토부, 2012)에 제시 된 4대강 유역의 ARF와 제주도 한천유역의 수문학적 특성을 반영한 ARF를 산정하여 비교 하였다. 표본면적($100km^2$)에 대하여 기존 4대강 유역의 ARF와 본 연구에서 산정된 ARF 비교 결과 권역별, 빈도별, 지속시간에 따른 ARF는 제주 도심지 유역 기준 최대 18.63%(영산강유역) 작게 산정되었음을 확인하였다. 이러한 결과는 향후 해당유역의 수문학적 특성 미반영으로 인해 설계홍수량이 과다 및 과소 산정되어 안정적인 수공구조물 결정을 저해하는 중요 요소로 작용 될 수 있어 제주도 전 유역에 적용 가능한 ARF 산정 및 기준 설정 등의 조치가 요구된다.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.17-17
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• 2019

IPCC (Intergovernmental Panel on Climate Change) 기후변화 전망보고서에 따르면 RCP 4.5 시나리오 기준, 21세기 전 지구 평균기온은 $2.5^{\circ}C$ 상승(한반도 $+3.0^{\circ}C$)하며, 전 지구 평균강수량은 4.1% 증가(한반도 +16.0%)할 것이라 전망하고 있다(기상청, 2012). 최근 기후변화와 기상이변에 따른 도심지 폭우특성이 변화하고 있음을 많은 연구결과에서 말해주고 있으며, 그 발생 빈도와 강도가 점차 증가하고 있는 추세이다. 특히, 서울시의 경우 인구와 재산이 밀집해 있어 폭우 발생에 의한 시민의 인명과 재산 피해 우려가 크다. 따라서 본 연구에서는 서울시를 대상으로 근미래(~2050년) 기후변화 하에서의 재현기간에 따른 확률강우량 변화 특성을 분석하여 비교 평가한 후 설계 강우량 산정에 활용하고자 하였다. 관측자료 기반 강수량의 변동 특성 분석과 Non-stationary GEV방법을 이용한 비정상성 빈도해석을 수행하였으며, 근미래 폭우특성 변화분석을 위하여 CMIP5 (Coupled Model Intercomparison Project 5)에 참여한 GCMs(General Circulation Models)을 활용한 강우빈도해석을 수행하였다. Mann-Kendall Test와 Quantile Regression을 통한 서울지점 여름철 강수량(June to September)과 기준강수량 초과 강수(30, 50, 80, 100mm/hr), 연간 10th 최대 강수량(Annual Top 10th Precipitation) 등을 분석한 결과 최근 증가 경향이 뚜렷하게 나타났으며, 비정상성 빈도해석에 의한 확률강우량 분석의 가능성과 신뢰성을 확인하였다. 또한 19-GCMs을 통하여 모의된 일(Daily) 단위 강수량자료를 비모수통계적 상세화(Nonparametric Temporal Downscaling) 기법을 적용하여 시간(Hourly) 강우로 다운스케일링하였으며, 서울시 미래 확률강우량에 대한 IDF 곡선(Intensity-Duration-Frequency Curve)을 작성하여 비교?분석한 결과 지속시간 1시간 강우에 대하여 재현기간 30년, 100년 조건에서 확률강우량이 약 4%~11% 수준에서 증가하고 있음을 확인하였다. 본 연구의 결과는 도심지 수공구조물의 설계빈도 영향을 진단하고, 근미래 발생가능한 확률강우량 변화에 따른 시간당 목표 강우량설정의 방법론을 제시하였다는데 의의가 있으며, 서울시의 방재성능목표 설정과 침수취약지역 해소를 위한 기후변화에 따른 수공구조물 설계 시 활용이 가능할 것으로 기대된다.